ABSTRACT Multiphoton microscopy is one of the preferred techniques for high-resolution functional brain imaging because of its remarkable depth penetration in thick tissue. In standard configurations, such imaging involves scanning a femtosecond laser focus in 3D throughout a sample. The laser power is fixed during the scan and image information is contained in the time dependence of the detected fluorescence signal. Several problems can occur with this technique. First, in common cases where the sample contains extreme variations in brightness, for example between large somas and much finer dendritic processes, it is often impossible to capture the full range of signals without either saturating the detector when scanning over bright regions, or losing signal when scanning over dim regions. Second, when imaging time-varying signals from functional reporters such as GCaMP, large brightness variations occur that cannot be predicted in advance, forcing the user to use a low illumination to minimize the possibility of detector saturation, thus potentially compromising SNR. Third, when performing volumetric scans through an extended range of depths, a single laser power becomes either too weak at large depths or too strong at shallow depths. We propose a simple solution to solve all these problems. The solution involves actively regulating the laser power pixel-by-pixel using feedback electronics. We have demonstrated that our technique can improve the dynamic range of two-photon microscopes by several orders of magnitude for moderately fast pixel times of 20?s, achieving an unprecedentedly high dynamic range (HDR) of 1011:1. Our goals for this project are the: 1) Development of ultrafast feedback electronics for video-rate HDR imaging. 2) Development of switched multiplexing technique for large-scale multi-region HDR imaging. 3) Application of multiphoton HDR imaging to anatomical and functional mouse brain imaging. Our goal is to enable comprehensive large-scale multiphoton imaging with unprecedented dynamic range in a simple manner that can be readily implementable by many labs at reasonable cost and with minimal hardware modifications.